probeInteraction {MDMA} | R Documentation |
Probe interaction models
Description
Probe the effect of a moderator on an X/antecedent variable in a linear model.
Usage
probeInteraction(
object,
antecedent,
moderator,
alpha = 0.05,
JN = TRUE,
n.interval.moderator,
quantile.moderator,
values.moderator
)
Arguments
object |
object of class |
antecedent |
antecedent (or x) variable in |
moderator |
moderator variable in |
alpha |
desired alpha level for Johnson-Neyman procedure. |
JN |
indicate whether Johnson-Neyman procedure should be carried out. |
n.interval.moderator |
number of intervals in the moderator variable to probe. |
quantile.moderator |
quantile values in the moderator variable to probe. |
values.moderator |
raw values in the moderator variable to probe. |
Details
the arguments n.interval.moderator
, quantile.moderator
and values.moderator
can be combined. All unique values from these methods combined, together with the values from the
Johnson-Neyman procedure (if specified) will be part of the probing procedure.
Value
probeInteraction
returns a data frame containing values of the moderator
in a linear model, the effect of the antecedent at that value of the moderator,
standard errors, t values, p values and a confidence interval.
Author(s)
Mathijs Deen
Examples
lm.1 <- lm(mpg ~ hp * wt, data = mtcars)
probeInteraction(lm.1, hp, wt, JN=TRUE, n.interval.moderator = 3,
quantile.moderator = c(0.1,0.9), values.moderator = 2)